In this study, monitoring and investigating the mining activities located in the forestry area and quantifying the environmental effect of these activities were carried out by means of orthophotos and satellite imageries. The study area consists of 4 open pit mines surrounded by forestry area located in the Antalya province which is nearby the Mediterranean Sea known as one of the most popular holiday destinations in Turkey. Opposite to the expansion of the mine areas forestry area decreases in this region. To quantify the decrease in the forestry area multi-temporal satellite imageries were used for 4 open pit mines. Used data were Spot 5 and Spot 6 satellite images with spatial resolution of 5 m and 6 m respectively. Spatial change was determined by applying object-based classification method for all satellite images. Accuracy analyses were made by means of overall accuracy and kappa statistic values. The overall accuracy values of the classified imageries of 2011, 2014 and 2017 were respectively 94.81%, 94.0% and 97.1% with the kappa statistical values of 0.9212, 0.9070 and 0.9538. According to the results of these classifications, the area values covered by the mines in the study area were respectively 55.06, 77.02 and 103.10 hectares in 2011, 2014 and 2017. Additionally, an unmanned aerial vehicle (UAV) was used in one of the mine areas in order to realistic evaluation of an area by using orthophotos. Two orthophotos with the pixel sizes of 4 cm and 7 cm were produced from multi-temporal aerial photographs. As a result of the study, it can be said that remotely sensed imageries are the main data to temporal follow-up of the mine areas. In this context, UAVs have been shown to be a better option for monitoring the environmental effects of mining areas when criteria such as acquisition of the data, accuracy, speed and time are evaluated. The difficulty of finding an optimal satellite image in terms of cost and different types of resolutions such as spatial, spectral, radiometric and temporal make the use of UAVs more prominent.